The Tech Policy Press Podcast How to Become an Algorithmic Problem
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Feb 22, 2026 José Marichal, a political scientist at California Lutheran University who writes on technology and politics, explores how algorithms reshape public life. He discusses outliers and democratic value, the idea of an implicit bargain with platforms, optimization’s squeeze on novelty, surveillance’s harm to community, and proposals like a right to serendipity and cultivating idiosyncrasy.
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Outliers Are Democratic Fuel
- Outliers matter because they destabilize predictive models and reveal what algorithms suppress.
- Marichal links statistical outliers to human novelty, arguing recommendation systems push people toward predictability to improve model fit.
The Algorithmic Contract Reduces Novelty
- The algorithmic contract trades unpredictability and novelty for curated convenience and reduced anxiety.
- Marichal frames platform curation as a bargain: platforms grant ordered experience while constraining potential and plural engagement.
AI Amplifies Modal Responses
- AI and recommendation systems push toward modal, predictable outputs that squeeze out novelty and anachronism.
- Marichal warns base LLMs act like sophisticated autocomplete, favoring average responses over creative divergence.
